Trajectory Drift–Compensated Solution of a Stereo RGB-D Mapping System

Abstract

Multiple sensors are commonly used for three-dimensional (3D)-mapping or robotic-vision applications, as they provide a larger field of view and sufficient observations to fulfill frame-registration and map-updating tasks. However, the data sequences generated by multiple sensors can be inconsistent and contain significant time drift. In this paper, we describe the trajectory drift–compensated strategy that we designed to eliminate the influence of time drift between sensors, remove the inconsistency between the sequences from various sensors, and thereby generate a coarse-to-fine procedure for robust camera-tracking based on two-dimensional–3D observations from stereo sensors. We present the mathematical analysis of the iterative optimizations for pose tracking in a stereo red, green, blue plus depth (RGB-D) camera. Finally, complex indoor scenario experiments demonstrate the efficiency of the proposed stereo RGB-D simultaneous localization and mapping solution. The results verify that the proposed stereo RGB-D mapping solution effectively improves the accuracies of both camera-tracking and 3D reconstruction.